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Automated diagnosis of epilepsy using EEG power spectrum
Author(s) -
Kerr Wesley T.,
Anderson Ariana,
Lau Edward P.,
Cho Andrew Y.,
Xia Hongjing,
Bramen Jennifer,
Douglas Pamela K.,
Braun Eric S.,
Stern John M.,
Cohen Mark S.
Publication year - 2012
Publication title -
epilepsia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.687
H-Index - 191
eISSN - 1528-1167
pISSN - 0013-9580
DOI - 10.1111/j.1528-1167.2012.03653.x
Subject(s) - electroencephalography , ictal , epilepsy , population , predictive value , medicine , psychiatry , environmental health
Summary Interictal electroencephalography (EEG) has clinically meaningful limitations in its sensitivity and specificity in the diagnosis of epilepsy because of its dependence on the occurrence of epileptiform discharges. We have developed a computer‐aided diagnostic (CAD) tool that operates on the absolute spectral energy of the routine EEG and has both substantially higher sensitivity and negative predictive value than the identification of interictal epileptiform discharges. Our approach used a multilayer perceptron to classify 156 patients admitted for video‐EEG monitoring. The patient population was diagnostically diverse; 87 were diagnosed with either generalized or focal seizures. The remainder of the patients were diagnosed with nonepileptic seizures. The sensitivity was 92% (95% confidence interval [CI] 85–97%) and the negative predictive value was 82% (95% CI 67–92%). We discuss how these findings suggest that this CAD can be used to supplement event‐based analysis by trained epileptologists.